Exploring Fog Computing-Based Adaptive Vehicular Data Scheduling Policies Through a Compositional Formal Method-PEPA
Exploring Fog Computing-Based Adaptive Vehicular Data Scheduling Policies Through a Compositional Formal Method-PEPA
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DOI：
10.1109/lcomm.2016.2647595
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发表时间：
2017-04-01
期刊：
影响因子：
--
通讯作者：
Wang, Liangmin
中科院分区：
文献类型：
--
作者：
Chen, Xiao;Wang, Liangmin
车载网络能够实现有效的通信，目的是改善车辆之间的数据传播。然而，越来越多的车辆希望通过路边设施进行数据传播，这导致网络负载增加。为了解决这个问题，这封信应用雾计算技术来增强计划作为分层网络架构的车辆网络。此外，提出了两个动态调度算法的雾计算方案的数据调度在车辆网络。这些算法可以动态地适应变化的网络环境，并在效率上受益。在性能分析方面，提出了一种性能评估过程代数的形式化方法，用于对基于雾的车载网络调度算法进行建模。
Vehicular networks enable an efficient communication with the aim of improving data dissemination among vehicles. However, a growing number of vehicles expect to conduct data dissemination through road side facilities which cause an increment of network load. To address the issue, this letter applies fog computing technologies for enhancing vehicular network that is planned as a layered network architecture. Moreover, two dynamic scheduling algorithms are proposed on the fog computing scheme for the data scheduling in vehicular networks. These algorithms can dynamically adapt a changeable network environment and benefit in efficiency. For performance analysis, a compositional formal method, named performance evaluation process algebra, is applied to model scheduling algorithm in a fog-based vehicular network.